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Found 4 papers, 1 papers with code
Feedforward neural networks as statistical models: Improving interpretability through uncertainty quantification
Feedforward neural networks (FNNs) are typically viewed as pure prediction algorithms, and their strong predictive performance has led to their use in many machine-learning applications.
A Statistical-Modelling Approach to Feedforward Neural Network Model Selection
Feedforward neural networks (FNNs) can be viewed as non-linear regression models, where covariates enter the model through a combination of weighted summations and non-linear functions.
An age-structured SEIR model for COVID--19 incidence in Dublin, Ireland with framework for evaluating health intervention cost
Strategies adopted globally to mitigate the threat of COVID-19 have primarily involved lockdown measures with substantial economic and social costs with varying degrees of success.
A Generalized Framework for Simultaneous Long-Short Feedback Trading
We present a generalization of the Simultaneous Long-Short (SLS) trading strategy described in recent control literature wherein we allow for different parameters across the short and long sides of the controller; we refer to this new strategy as Generalized SLS (GSLS).
